Instructions to use solidrust/Mixtral_AI_TinyTronVision-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use solidrust/Mixtral_AI_TinyTronVision-AWQ with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="solidrust/Mixtral_AI_TinyTronVision-AWQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("solidrust/Mixtral_AI_TinyTronVision-AWQ")
model = AutoModelForCausalLM.from_pretrained("solidrust/Mixtral_AI_TinyTronVision-AWQ")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use solidrust/Mixtral_AI_TinyTronVision-AWQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "solidrust/Mixtral_AI_TinyTronVision-AWQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Mixtral_AI_TinyTronVision-AWQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/solidrust/Mixtral_AI_TinyTronVision-AWQ

SGLang

How to use solidrust/Mixtral_AI_TinyTronVision-AWQ with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "solidrust/Mixtral_AI_TinyTronVision-AWQ" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Mixtral_AI_TinyTronVision-AWQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "solidrust/Mixtral_AI_TinyTronVision-AWQ" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Mixtral_AI_TinyTronVision-AWQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use solidrust/Mixtral_AI_TinyTronVision-AWQ with Docker Model Runner:
```
docker model run hf.co/solidrust/Mixtral_AI_TinyTronVision-AWQ
```

Mixtral_AI_TinyTronVision-AWQ

Commit History

Added base_model tag in README.md

3a4ff96
verified

Suparious commited on Sep 3, 2024

Update README.md

b26b7bf
verified

Suparious commited on Apr 21, 2024

Update README.md

b74acaf
verified

Suparious commited on Apr 21, 2024

adding initial model card

55bcbcb

Ubuntu commited on Apr 19, 2024

adding quant config

e6f4835

Ubuntu commited on Apr 19, 2024

adding AWQ model

f5949b5

Ubuntu commited on Apr 19, 2024

initial commit

b8fc37d
verified

Suparious commited on Apr 19, 2024

Commit History

Added base_model tag in README.md 3a4ff96 verified

Update README.md b26b7bf verified

Update README.md b74acaf verified

adding initial model card 55bcbcb

adding quant config e6f4835

adding AWQ model f5949b5

initial commit b8fc37d verified

Added base_model tag in README.md

3a4ff96
verified

Update README.md

b26b7bf
verified

Update README.md

b74acaf
verified

adding initial model card

55bcbcb

adding quant config

e6f4835

adding AWQ model

f5949b5

initial commit

b8fc37d
verified